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Showing 1,681 - 1,700 results of 2,743 for search '(improved OR improve) ((cost OR root) OR post) optimization algorithm', query time: 0.30s Refine Results
  1. 1681

    Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

    Published 2009-01-01
    “…It’s an important way to guarantee QoS for the next generation network(NGN) with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
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    Article
  2. 1682

    Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

    Published 2009-01-01
    “…It’s an important way to guarantee QoS for the next generation network(NGN) with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
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    Article
  3. 1683

    Energy Storage Configuration Optimization of a Wind–Solar–Thermal Complementary Energy System, Considering Source-Load Uncertainty by Guangxiu Yu, Ping Zhou, Zhenzhong Zhao, Yiheng Liang, Weijun Wang

    Published 2025-07-01
    “…Simulation verification in a certain region shows that the proposed method reduces comprehensive cost by 8.9%, operation cost by 10.3%, the curtailment rate of wind and solar energy by 8.92%, and carbon emissions by 3.51%, which significantly improves the economy and low-carbon performance of the system and provides a reference for the future planning and operation of energy systems.…”
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  4. 1684

    Network Optimization of Fresh Products Cold Chain Considering Supply Disruption and Demand Fluctuation Under the Dual-Carbon Policy by Haojie Ran, Dichen He, Huajun Tang

    Published 2025-05-01
    “…The research results provide valuable decision-making support for fresh cold chain enterprises to develop resilient and low-carbon network optimization strategies for cost reduction, efficiency improvement, and sustainable development.…”
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  5. 1685

    Layout optimization of multi-level cold chain storage facilities in agricultural producing areas considering type and capacity constraints. by Qian Huang, Guijun Zheng, Shuangli Pan, Huiyu Liao, Zehua Jiang

    Published 2025-01-01
    “…Based on the above considerations, with the aim of minimizing the total daily cost, an optimization model for the layout of multi-level cold chain storage facilities is established to determine the number, location, type and capacity of cold chain storage facilities at the same time. …”
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  6. 1686

    Meta-RHDC: Meta Reinforcement Learning Driven Hybrid Lyrebird Falcon Optimization for Dynamic Load Balancing in Cloud Computing by Mallu Shiva Rama Krishna, D. Khasim Vali

    Published 2025-01-01
    “…By integrating reinforcement learning with advanced optimization techniques, Meta-RHDC significantly improves task scheduling and load balancing compared to existing methods such as Load Optimization Algorithm (LOA), Reinforcement Learning (RL), and Falcon Optimization Algorithm (FOA). …”
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    Article
  7. 1687
  8. 1688

    Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

    Published 2024-11-01
    “…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
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  9. 1689

    Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

    Published 2025-05-01
    “…With the widespread adoption of electric vehicles (EVs), optimizing their charging and discharging strategies to improve energy efficiency and extend battery life has become a focal point of current research. …”
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  10. 1690

    Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

    Published 2025-01-01
    “…The application of GWO for hyperparameter tuning has resulted in a 37.3% reduction in root mean square error (RMSE), a 37.4% drop in mean absolute percentage error (MAPE), and a 2.06% improvement in <inline-formula> <tex-math notation="LaTeX">$\text {R}^{2}$ </tex-math></inline-formula> to improve the precision of prediction. …”
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  11. 1691
  12. 1692

    A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks by Jhony Andrés Guzmán-Henao, Rubén Iván Bolaños, Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Jesús C. Hernández

    Published 2024-12-01
    “…Its master stage uses one out of three different algorithms—Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), or the Multi-Objective Ant Lion Optimizer (MOALO)—while the slave stage is always performed by a load flow analyzer. …”
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  13. 1693

    Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

    Published 2025-04-01
    “…Results demonstrate the effectiveness of predictive analytics in improving supply chain quality management, enabling enterprises to proactively reduce defect rates, minimize costs, and optimize return on investment (ROI). …”
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  14. 1694

    Enhanced Stability and Performance of Islanded DC Microgrid Systems Using Optimized Fractional Order Controller and Advanced Energy Management by Md. Wahidujjaman, Tasnim Ul Bari, Md. Shafiul Alam, Md. Rashidul Islam, Md. Alamgir Hossain, Md. Arafat Hossain, Md. Rafiqul Islam Sheikh

    Published 2025-04-01
    “…To address these issues, this study proposes the use of an optimized fractional order PI (FOPI) controller and an efficient energy management algorithm. …”
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  15. 1695

    Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

    Published 2025-01-01
    “…Notably, the Thermal Exchange Optimization (TEO) algorithm resulted in the most significant improvement, increasing the accuracy of the original SVM model by 10% and exceeding the standard by 4.3%. …”
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  16. 1696

    Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration by Junxian Li, Jiaxin Yuan, Xuxin Yue

    Published 2025-09-01
    “…This efficient strategy consists of the inherent complexities, which is solved by the NSGA-II algorithm. The multi-objective approach of optimization procedure performs Pareto solution sets that reflects trade-offs between remaining load variations and operational costs. …”
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  17. 1697

    Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators by Qin Yan, Jinxin Wang, Tao Lin, Archie James Johnston

    Published 2025-08-01
    “…Simulation results show that the proposed model improves grid resilience, enhances economic benefits for both aggregators and users, and optimizes the system’s performance. …”
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  18. 1698

    Optimized Design and Deep Vision-Based Operation Control of a Multi-Functional Robotic Gripper for an Automatic Loading System by Yaohui Wang, Sheng Guo, Jinliang Zhang, Hongbo Ding, Bo Zhang, Ao Cao, Xiaohu Sun, Guangxin Zhang, Shihe Tian, Yongxu Chen, Jixuan Ma, Guangrong Chen

    Published 2025-05-01
    “…A deep vision-based recognition system, enhanced by an improved YOLOv5 algorithm and multi-feature fusion, was employed for real-time object detection and pose estimation. …”
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  19. 1699

    Joint Optimization of Berths and Quay Cranes Considering Carbon Emissions: A Case Study of a Container Terminal in China by Houjun Lu, Xiao Lu

    Published 2025-01-01
    “…This study presents an integrated model that incorporates tidal factors into the joint optimization of berth and quay crane operations, addressing both service standards and emissions during port stays and crane activities, and further designs a PSO-GA hybrid algorithm, combining particle swarm optimization (PSO) with crossover and mutation operators from a genetic algorithm (GA), to enhance optimization accuracy and efficiency. …”
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    Article
  20. 1700

    Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

    Published 2025-04-01
    “…A genetic algorithm was employed for single-objective optimization targeting three criteria: maximizing total efficiency, minimizing pressure drop, and maximizing the Nusselt number. …”
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